Introduction to Modern Information Retrieval
Introduction to Modern Information Retrieval
Toward Automatic Simulation of Aging Effects on Face Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Logic, Knowledge Representation, and Bayesian Decision Theory
CL '00 Proceedings of the First International Conference on Computational Logic
Friendster and publicly articulated social networking
CHI '04 Extended Abstracts on Human Factors in Computing Systems
Semantic Web Link Analysis to Discover Social Relationships in Academic Communities
SAINT '05 Proceedings of the The 2005 Symposium on Applications and the Internet
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Boosting Sex Identification Performance
International Journal of Computer Vision
POLYPHONET: An advanced social network extraction system from the Web
Web Semantics: Science, Services and Agents on the World Wide Web
Combining Collective Classification and Link Prediction
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
Automated social hierarchy detection through email network analysis
Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and social network analysis
Measuring social networks with digital photograph collections
Proceedings of the nineteenth ACM conference on Hypertext and hypermedia
Annotation suggestion and search for personal multimedia objects on the web
CIVR '08 Proceedings of the 2008 international conference on Content-based image and video retrieval
Extracting Social Networks Among Various Entities on the Web
ESWC '07 Proceedings of the 4th European conference on The Semantic Web: Research and Applications
Structural reproduction of social networks in computer-mediated communication forums
Behaviour & Information Technology
Mining and Visualizing Mobile Social Network Based on Bayesian Probabilistic Model
UIC '09 Proceedings of the 6th International Conference on Ubiquitous Intelligence and Computing
Linking social networks on the web with FOAF: a semantic web case study
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Extracting keyphrases to represent relations in social networks from web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Close & closer: social cluster and closeness from photo collections
MM '09 Proceedings of the 17th ACM international conference on Multimedia
An Algorithm of Mining Class Association Rules
ISICA '09 Proceedings of the 4th International Symposium on Advances in Computation and Intelligence
Flink: Semantic Web technology for the extraction and analysis of social networks
Web Semantics: Science, Services and Agents on the World Wide Web
Labeling categories and relationships in an evolving social network
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Consumer image retrieval by estimating relation tree from family photo collections
Proceedings of the ACM International Conference on Image and Video Retrieval
Mining advisor-advisee relationships from research publication networks
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
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In this paper, we propose a new approach to discover the relationship types between a user and her contacts in a social network. This is of key importance for many applications in the domain of photo sharing, privacy protection, information enriching, etc. Our approach is based, on one hand, on information extracted from users' profiles and their shared photos, and, on the other hand, on a set of predefined rules validated by the main user before being mined and derived according to her preferences and social network content. The contribution of our method is twofold: 1) it is user-based enabling the user to set her preferences and give her feedbacks on the derived rules and results, and 2) it is multi-criteria that exploits and combines several attributes and features from user profiles and shared photos respectively. It also allows the user to define new relationship types. We conducted a set of experiments to validate our approach. The obtained results show the accuracy of our approach in different scenarios.